Generative Pre-trained Transformer (GPT) is a deep neural network architecture used for natural language processing (NLP) and text generation. It was developed by OpenAI and uses a machine learning technique known as "transformer", which is based on attention and parallel processing.
The most recent version of the architecture, GPT-3, is one of the largest and most advanced natural language models available, with 175 billion parameters. GPT-3 is trained on a massive text corpus to learn the structure of language and the relationship between words and sentences. Once trained, the model can be used to complete sentences, translate languages, answer questions and generate text.
GPT-3 is also capable of performing more complex tasks, such as article writing, story creation and code generation. Unlike traditional NLP models, GPT-3 does not require a specific task to be trained, but can be used for a variety of text generation tasks.
Companies are increasingly aware of the importance of properly analyzing and managing the huge amount of data they store on a daily basis.
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